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Estimation of electricity demand of Iran using two heuristic algorithms

Authors :
Amjadi, M.H.
Nezamabadi-pour, H.
Farsangi, M.M.
Source :
Energy Conversion & Management. Mar2010, Vol. 51 Issue 3, p493-497. 5p.
Publication Year :
2010

Abstract

Abstract: This paper deals with estimation of electricity demand of Iran based on economic indicators using Particle Swarm Optimization (PSO) Algorithm. The estimation is based on Gross Domestic Product (GDP), population, number of customers and average price electricity by developing two different estimation models: a linear model and a non-linear model. The proposed models are obtained based upon available actual data of 21years; since 1980–2000. Then the models obtained are used to estimate the electricity demand of the target years; for a period of time e.g. 2001–2006 and the results obtained are compared with the actual demand during this period. Furthermore, to validate the results obtained by PSO, genetic algorithm (GA) is applied to solve the problem. The results show that the PSO is a useful optimization tool for solving the problem using two developed models and can be used as an alternative solution to estimate the future electricity demand. [Copyright &y& Elsevier]

Details

Language :
English
ISSN :
01968904
Volume :
51
Issue :
3
Database :
Academic Search Index
Journal :
Energy Conversion & Management
Publication Type :
Academic Journal
Accession number :
47053487
Full Text :
https://doi.org/10.1016/j.enconman.2009.10.013